Institute of Energy Technologies – Fundamental Electrochemistry (IET-1)

The dataverse of the Institute of Energy Technologies – Fundamental Electrochemistry (IET-1), formerly Institute of Energy and Climate Research (IEK-9)

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1,791 to 1,800 of 1,893 Results

README.txt Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers' Plain Text - 2.9 KB - SHA-256: 04d698fcbcc24d01410c2bbea13a00d3b990f410bc0cea47c9ddbd9d86692413
SOAP_ERT_MODEL.pkl Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers' Unknown - 692.3 KB - SHA-256: dd8c7bce0004d614fd59b058e9bab2903c262795b497b2cdc3e920ef293bdbb9
TE1_giso_DFT_data.npy Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers' Unknown - 1.2 KB - SHA-256: 5114ade6cef2a056e9ea94fc984b760d594708f635b79f9249a36cc32fddbb95
TOC.png Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers' PNG Image - 124.8 KB - SHA-256: 47056b6a59f2007d7234fc918be34dee983af07cab83b205b19910dfebfcda1e
train_giso_DFT_data.npy Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers' Unknown - 1.3 KB - SHA-256: 812c9b42df9714ae3d31fb6a15c305ce61b675e421c51ddfe082f35288eb0677
train_structure_data_DAD.npy Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers' Unknown - 873.2 KB - SHA-256: 2990b97521555d990f6a6c64a15e20273efa5ab0ede53675e0d7c7ef2d368dd1
train_structure_data_MBTR.npy Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers' Unknown - 3.1 MB - SHA-256: 8b4236ffcbeb2064aae439cb1c43be5ed7f76b09498a6f0b1543fbab4f72eb02
train_structure_data_SOAP.npy Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers' Unknown - 5.4 MB - SHA-256: 06e2a52689d4971d5e07f9e43a97792750baecd815d00095a40844b46169b181
Replication Data and Matlab Code for: StructureHyperfineRelations May 22, 2023 - Spectroscopy Szczuka, Conrad; Rüdiger-A. Eichel; Josef Granwehr, 2023, "Replication Data and Matlab Code for: StructureHyperfineRelations", https://doi.org/10.26165/JUELICH-DATA/UH0LM2, Jülich DATA, V1 Supporting data and scripts to the publication "Gauging the importance of structural parameters for hyperfine coupling constants in organic radicals". In the accompanying publication, we present a procedure based on a statistical approach to gauge the importance of structure para...
A_DataPreparation.m May 22, 2023 - Replication Data and Matlab Code for: StructureHyperfineRelations MATLAB Source Code - 2.6 KB - SHA-256: 8c703a60c9094df530d4bbc19d6b9c74afeea7bb9bd47796f5de1040d3969e30

README.txt

Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers'

Plain Text - 2.9 KB - SHA-256: 04d698fcbcc24d01410c2bbea13a00d3b990f410bc0cea47c9ddbd9d86692413

SOAP_ERT_MODEL.pkl

Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers'

Unknown - 692.3 KB - SHA-256: dd8c7bce0004d614fd59b058e9bab2903c262795b497b2cdc3e920ef293bdbb9

TE1_giso_DFT_data.npy

Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers'

Unknown - 1.2 KB - SHA-256: 5114ade6cef2a056e9ea94fc984b760d594708f635b79f9249a36cc32fddbb95

TOC.png

Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers'

PNG Image - 124.8 KB - SHA-256: 47056b6a59f2007d7234fc918be34dee983af07cab83b205b19910dfebfcda1e

train_giso_DFT_data.npy

Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers'

Unknown - 1.3 KB - SHA-256: 812c9b42df9714ae3d31fb6a15c305ce61b675e421c51ddfe082f35288eb0677

train_structure_data_DAD.npy

Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers'

Unknown - 873.2 KB - SHA-256: 2990b97521555d990f6a6c64a15e20273efa5ab0ede53675e0d7c7ef2d368dd1

train_structure_data_MBTR.npy

Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers'

Unknown - 3.1 MB - SHA-256: 8b4236ffcbeb2064aae439cb1c43be5ed7f76b09498a6f0b1543fbab4f72eb02

train_structure_data_SOAP.npy

Mar 11, 2024 - Replication Data and Code for: 'Machine learning isotropic g values of radical polymers'

Unknown - 5.4 MB - SHA-256: 06e2a52689d4971d5e07f9e43a97792750baecd815d00095a40844b46169b181

Replication Data and Matlab Code for: StructureHyperfineRelations

May 22, 2023 - Spectroscopy

Szczuka, Conrad; Rüdiger-A. Eichel; Josef Granwehr, 2023, "Replication Data and Matlab Code for: StructureHyperfineRelations", https://doi.org/10.26165/JUELICH-DATA/UH0LM2, Jülich DATA, V1

Supporting data and scripts to the publication "Gauging the importance of structural parameters for hyperfine coupling constants in organic radicals". In the accompanying publication, we present a procedure based on a statistical approach to gauge the importance of structure para...

A_DataPreparation.m

May 22, 2023 - Replication Data and Matlab Code for: StructureHyperfineRelations

MATLAB Source Code - 2.6 KB - SHA-256: 8c703a60c9094df530d4bbc19d6b9c74afeea7bb9bd47796f5de1040d3969e30

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